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Curating genes and genomesApollo: a collaborative tool for genome curation
Monica Munoz-Torres, PhD | @monimunozto
Berkeley Bioinformatics Open-Source Projects (BBOP)Lawrence Berkeley National Laboratory | University of California Berkeley | U.S. Department of Energy
BioInfoGenomicsWkshopv2 | Reed College, Portland, Oregon | 10 October, 2015
OUTLINE
Web Apollo Collabora've Cura'on and Interac've Analysis of Genomes
2 OUTLINE
• Today we will discover how to extract the most valuable informa'on about a genome through cura'on efforts.
APOLLO DEVELOPMENT
APOLLO DEVELOPERS 3
h*p : / /GenomeA r c h i t e c t . o r g /
Nathan Dunn
Eric Yao JBrowse, UC Berkeley
Christine Elsik’s Lab, University of Missouri
Suzi Lewis Principal Investigator
BBOP
Moni Munoz-Torres
Stephen Ficklin GenSAS,
Washington State University
Colin Diesh Deepak Unni
4
BY THE END OF THIS TALKyou will
v Be@er understand genome cura'on in the context of annota'on: assembled genome à automated annota=on à manual annota=on
v Become familiar with the environment and func'onality of the Apollo genome annota'on edi'ng tool.
v Learn to iden'fy homologs of known genes of interest in a newly sequenced genome.
v Learn about corrobora'ng and modifying automa'cally annotated gene models using available evidence in Apollo.
What to expect
Anatomy of a genome sequencing project
6
Genome Sequencing Project
Anatomy of a genome sequencing project
Experimental design, sampling.
Comparative analyses
Consensus Gene Set
Manual Annotation
Automated Annotation
Sequencing Assembly
Synthesis & dissemination.
CURATING GENOMESsteps involved
1 Genera=on of Gene Models calling ORFs, one or more rounds of gene predic'on, etc.
2 Annota=on of gene models Describing func'on, expression pa@erns, metabolic network memberships.
3 Manual annota=on
CURATING GENOMES 7
GENOME ANNOTATIONobjectives and uses
Curating Genomes 8
The gene set of an organism informs a variety of studies: • Gene number, GC%, TE composi'on, repe''ve regions. • Func'onal assignments.
• Molecular evolu'on, sequence conserva'on. • Gene families. • Metabolic pathways. • What makes an organism what it is?
What makes a bee a “bee”?
Marbach et al. 2011. Nature Methods | Shutterstock.com | Alexander Wild
First, a bio-‐refresher
WHAT WE NEED TO KNOWfor manual annotation
To remember… Biological concepts to be@er understand manual annota'on
10 FOOD FOR THOUGHT
• GLOSSARY from con1g to splice site
• CENTRAL DOGMA
in molecular biology • WHAT IS A GENE?
defining your goal
• TRANSCRIPTION mRNA in detail
• TRANSLATION
and other defini'ons
• GENOME CURATION steps involved
11 CURATING GENOMES
WHAT WE KNOWin very general terms
12 CURATING GENOMES
WHAT WE KNOWin very general terms
http://www.wisegeek.com/
5’
3’
5’
3’
13 CURATING GENOMES
CENTRAL “DOGMA”of molecular biology
v DNA can be copied to DNA (DNA replica'on),
v DNA informa'on can be copied into mRNA (transcrip'on), and
v Proteins can be synthesized using the informa'on in mRNA as a template (transla'on).
http://www.wisegeek.com/
14 BIO-REFRESHER
What is a gene?
v The defini'on of a gene paints a very complex picture of molecular ac'vity and it is a con'nuously evolving concept.
• From the Sequence Ontology (SO): “A gene is a locatable region of genomic sequence, corresponding to a unit of inheritance, which is associated with regulatory regions, transcribed regions and/or other func'onal sequence regions”. “Evolving Concept” at h@p://goo.gl/LpsajQ
15 BIO-REFRESHER
What is a gene?
v In your life'me, the Encyclopedia of DNA Elements (ENCODE) project updated this concept yet again. Long transcripts & dispersed regula1on!
“A gene is a DNA segment that contributes to phenotype/func'on. In the absence of demonstrated func'on, a gene may be characterized by sequence, transcrip'on or homology.”
https://www.encodeproject.org/
16 BIO-REFRESHER
What is a gene?let’s think computationally!
v Think of the genome as an operating system for a living being
• Considering that the nucleo'des of the genome are put together into a code that is executed through the process of transcription and translation…
• … think of genes as subroutines that are repe''vely called in the process of transcription
Gerstein et al., 2007. Genome Res.
17 BIO-REFRESHER
What is a gene?considerations
v Also consider : • A gene is a genomic sequence (DNA or RNA) directly encoding
func'onal product molecules, either RNA or protein.
• If several func'onal products share overlapping regions, we take the union of all overlapping genomics sequences coding for them.
• This union must be coherent – i.e., processed separately for final protein and RNA products – but does not require that all products necessarily share a common subsequence.
Gerstein et al., 2007. Genome Res.
18 BIO-REFRESHER
“The gene is a union of genomic sequences encoding a coherent set of poten'ally
overlapping func'onal products.”
Gerstein et al., 2007. Genome Res
The Gene: a moving target.
What is a gene?
19 BIO-REFRESHER
TRANSLATIONreading frame
v Reading frame is a manner of dividing the sequence of nucleo'des in mRNA (or DNA) into a set of consecu've, non-‐overlapping triplets (codons).
v Three frames can be read in the 5’ à 3’ direc'on. Given that DNA has two an'-‐parallel strands, an addi'onal three frames are possible to be read on the an'-‐sense strand. Six total possible reading frames exist.
v In eukaryotes, only one reading frame per sec'on of DNA is biologically relevant at a 'me: it has the poten'al to be transcribed into RNA and translated into protein. This is called the OPEN READING FRAME (ORF) • ORF = Start signal + coding sequence (divisible by 3) + Stop signal
v The sec'ons of the mature mRNA transcribed with the coding sequence but not translated are called UnTranslated Regions (UTR); one at each end.
20
"Reading Frame" by Hornung Ákos - Wikimedia Commons
BIO-REFRESHER
TRANSLATIONreading frame
21
"ORF" by Thatsonginc - Wikimedia Commons
BIO-REFRESHER
TRANSLATIONreading frame
22 BIO-REFRESHER
TRANSLATIONreading frame: splice sites
v The spliceosome catalyzes the removal of introns and the liga'on of flanking exons. • introns: spaces inside the gene, not part of the coding sequence • exons: expression units (of the coding sequence)
v Splicing “signals” (from the point of view of an intron): • There is a 5’ end splice “signal” (site): usually GT (less common: GC) • And a 3’ end splice site: usually AG • …]5’-‐GT/AG-‐3’[…
v It is possible to produce more than one protein (polypep'de) sequence from the same genic region, by alterna'vely bringing exons together= alterna=ve splicing. For example, the gene Dscam (Drosophila) has 38,000 alterna'vely spliced mRNAs = isoforms
23
"Gene structure" by Daycd- Wikimedia Commons
BIO-REFRESHER
TRANSLATIONnow in your mind
• Although of brief existence, understanding mRNAs is crucial, as they will become the center of your work.
24 BIO-REFRESHER
TRANSLATIONreading frame: phase
v Introns can interrupt the reading frame of a gene by inser'ng a sequence between two consecu've codons
v Between the first and second nucleo'de of a codon
v Or between the second and third nucleo'de of a codon
"Exon and Intron classes”. Licensed under Fair use via Wikipedia
25
"Protein synthesis" by Kelvinsong - Wikimedia Commons
CURATING GENOMES
TRANSLATIONin detail
26 BIO-REFRESHER
HICCUPSin transcription and translation
v The presence of premature Stop codons in the message is possible. A process called non-‐sense mediated decay checks for them and corrects them to avoid: incomplete splicing, DNA muta'ons, transcrip'on errors, and leaky scanning of ribosome – causing changes in the reading frame (frame shiYs).
v Inser'ons and dele'ons (indels) can cause frame shijs, when indel is not divisible by three (3). As a result, the pep'de can be abnormally long, or abnormally short – depending when the first in-‐frame Stop signal is located.
Predic'on & Annota'on
28 Gene Prediction
GENE PREDICTION
v The iden'fica'on of structural features of the genome:
• Primarily focused on protein-‐coding genes. • Predicts also transfer RNAs (tRNA), ribosomal RNAs (rRNA),
regulatory mo'fs, long and small non-‐coding RNAs (ncRNA), repe''ve elements (masked), etc.
• Two methods for iden'fica'on. • Some are self-‐trained and some must be trained.
29 Gene Prediction
GENE PREDICTIONmethods for discovery
1) Ab ini,o: -‐ based on DNA composi'on, -‐ deals strictly with genomic sequences -‐ makes use of sta's'cal approaches to search for coding regions and typical gene signals. • E.g. Augustus, GENSCAN,
geneid, fgenesh, etc.
3’
Nat Rev Genet. 2015 Jun;16(6):321-32. doi: 10.1038/nrg3920
30
Nucleic Acids 2003 vol. 31 no. 13 3738-3741
Gene Prediction
GENE PREDICTIONmethods for discovery (ctd)
2) Homology-‐based: -‐ evidence-‐based, -‐ finds genes using either similarity searches in the main databases or experimental data including RNAseq, expressed sequence tags (ESTs), full-‐length complementary DNAs (cDNAs), etc.
• E.g: fgenesh++, Just Annotate My genome (JAMg), SGP2
31
GENE ANNOTATION
Integra'on of data from computa'onal & experimental evidence with data from predic'on tools, to generate a reliable set of structural annota=ons. Involves: 1) ab ini1o predic'ons 2) assessment of biological evidence to drive the gene predic'on process 3) synthesis of these results to produce a set of consensus gene models
Gene Annotation
32
In some cases algorithms and metrics used to generate consensus sets may actually reduce the accuracy of the gene’s representa'on.
GENE ANNOTATION
Gene models may be organized into “sets” using: v automa'c integra'on of predicted sets (combiners); e.g: GLEAN,
EvidenceModeler or
v tools packaged into pipelines; e.g: MAKER, PASA, Gnomon, Ensembl, etc.
Gene Annotation
ANNOTATIONan imperfect art
No one is perfect, least of all automated annotation. 33
New technology brings new challenges: • Assembly errors can cause fragmented
annota'ons • Limited coverage makes precise
iden'fica'on a difficult task
Image: www.BroadInstitute.org
MANUAL ANNOTATIONimproving predictions
Precise elucida=on of biological features encoded in the genome requires careful
examina=on and review.
Schiex et al. Nucleic Acids 2003 (31) 13: 3738-‐3741
Automated Predictions
Experimental Evidence
Manual Annotation – to the rescue. 34
cDNAs, HMM domain searches, RNAseq, genes from other species.
35
BIOCURATIONstructural and functional adjustments
Iden=fies elements that best represent the underlying biology and eliminates elements that reflect systemic errors of automated analyses.
Assigns func=on through compara've analysis of similar genome elements from closely related species using literature, databases, and experimental data.
MANUAL ANNOTATION
h@p://GeneOntology.org
1
2
GENOME ANNOTATIONan inherently collaborative task
APOLLO 36
Researchers oDen turn to colleagues for second opinions and insight from those with exper1se in
par1cular areas (e.g., domains, families).
So many sequences, but not enough hands!
APOLLOcollaborative genome annotation editing tool
37
v Web based, integrated with JBrowse. v Supports real 'me collabora'on! v Automa'c genera'on of ready-‐made
computable data. v Supports annota'on of genes, pseudogenes,
tRNAs, snRNAs, snoRNAs, ncRNAs, miRNAs, TEs, and repeats.
v Intui've annota'on, gestures, and pull-‐down menus to create and edit transcripts and exons structures, insert comments (CV, freeform text), associate GO terms, etc.
APOLLO
h@p://GenomeArchitect.org
APOLLO ARCHITECTUREsimple, flexible
ARCHITECTURE 38
Web-‐based client + annota'on-‐edi'ng engine + server-‐side data service
REST / JSON Websockets
Annotation Engine (Server)
Shiro
LDAP
OAuth
JBrowse Data Organism 2
Annotations
Security
Preferences
Organisms
Tracks
BAM BED VCF GFF3 BigWig
Annotators
Google Web Toolkit (GWT) / Bootstrap
JBrowse DOJO / jQuery JBrowse Data Organism 1
Load genomic evidence per selected organism
Single Data Store PostgreSQL, MySQL,
MongoDB, ElasticSearch
Apollo v2.0
We con'nuously train and support hundreds of geographically dispersed scien'sts from diverse research communi'es in conduc'ng manual annota'ons efforts to recover coding sequences in agreement with all available biological evidence using Apollo.
39
LESSONS LEARNED
APOLLO
What we have learned: • Collabora've work dis'lls invaluable knowledge • We must enforce strict rules and formats • We must evolve with the data • NGS poses addi'onal challenges
40
TRAINING CURATORSa little training goes a long way!
Provided with adequate tools, wet lab scien'sts make excep'onal curators who can easily learn to maximize the genera'on of accurate, biologically supported gene models.
APOLLO
Apollo
42
APOLLOannotation editing environment
BECOMING ACQUAINTED WITH APOLLO
Color by CDS frame, toggle strands, set color scheme and highlights.
Upload evidence files (GFF3, BAM, BigWig), add combina=on and sequence search tracks.
Query the genome using BLAT.
Naviga'on and zoom.
Search for a gene model or a scaffold.
Get coordinates and “rubber band” selec'on for zooming.
Login
User-‐created annota'ons. Annotator
panel.
Evidence Tracks
Stage and cell-‐type specific transcrip'on data.
h@p://genomearchitect.org/web_apollo_user_guide
Let’s play!
Instructions 44 | 44
APOLLO ON THE WEBinstructions
Username: [email protected]
Password: usernumber
Email Password Server Begin at [email protected] userone 1 1 [email protected] usertwo 2 1 [email protected] userthree 3 1 [email protected] userfour 4 1 [email protected] userfive 5 1 [email protected] usersix 1 7 [email protected] userseven 2 7 [email protected] usereight 3 7 [email protected] usernine 4 7 [email protected] userten 5 7 [email protected] usereleven 1 1 [email protected] usertwelve 2 1 [email protected] userthirteen 3 1 [email protected] userfourteen 4 1 [email protected] userfijeen 5 1 [email protected] usersixteen 1 7 [email protected] userseventeen 2 7 user.eigh@[email protected] usereighteen 3 7 [email protected] usernineteen 4 7 [email protected] usertwenty 5 7 [email protected] usertwentyone 1 1 [email protected] usertwentytwo 2 1 [email protected] usertwentythree 3 1 [email protected] usertwentyfour 4 1 [email protected] usertwentyfive 5 1 [email protected] usertwentysix 1 7 [email protected] usertwentyseven 2 7 [email protected] usertwentyeight 3 7 [email protected] usertwentynine 4 7
Server URL 1 h@p://52.26.7.239:8080/apollo/annotator/index 2 h@p://52.89.205.105:8080/apollo/annotator/index 3 h@p://52.89.230.210:8080/apollo/annotator/index 4 h@p://52.89.149.42:8080/apollo/annotator/index 5 h@p://52.89.233.118:8080/apollo/annotator/index
Cura'ng with Apollo
Becoming Acquainted with Web Apollo 46 | 46
GENERAL PROCESS OF CURATIONmain steps to remember
1. Select or find a region of interest, e.g. scaffold. 2. Select appropriate evidence tracks to review the gene model.
3. Determine whether a feature in an exis'ng evidence track will provide a reasonable gene model to start working.
4. If necessary, adjust the gene model.
5. Check your edited gene model for integrity and accuracy by comparing it with available homologs.
6. Comment and finish.
USER NAVIGATIONremovable side dock
HIGHLIGHTED IMPROVEMENTS 47
Annotations Organism Users Groups Admin Tracks Reference Sequence
EDITS & EXPORTSannotation details, exon boundaries, data export
HIGHLIGHTED IMPROVEMENTS 48
1 2
Annotations
1
2
HIGHLIGHTED IMPROVEMENTS 49
Reference Sequences
3
FASTA
GFF3
EDITS & EXPORTSannotation details, exon boundaries, data export
3
50 | 50 Becoming Acquainted with Web Apollo.
USER NAVIGATION
Annotator panel.
• Choose appropriate evidence from list of “Tracks” on annotator panel.
• Select & drag elements from evidence track into the ‘User-‐created Annota1ons’ area.
• Hovering over annota'on in progress brings up an informa'on pop-‐up.
• Crea'ng a new annota'on
51 | 51
USER NAVIGATION
Becoming Acquainted with Web Apollo.
• Annota'on right-‐click menu
52 | 52
USER NAVIGATION
Becoming Acquainted with Web Apollo.
• ‘Zoom to base level’ op'on reveals the DNA Track.
53 | 53
USER NAVIGATION
Becoming Acquainted with Web Apollo.
• Color exons by CDS from the ‘View’ menu.
54 |
Zoom in/out with keyboard: shij + arrow keys up/down
54
USER NAVIGATION
Becoming Acquainted with Web Apollo.
• Toggle reference DNA sequence and transla=on frames in forward strand. Toggle models in either direc'on.
Annota'on
simple cases
“Simple case”: -‐ the predicted gene model is correct or nearly correct, and
-‐ this model is supported by evidence that completely or mostly agrees with the predic'on.
-‐ evidence that extends beyond the predicted model is assumed to be non-‐coding sequence.
The following are simple modifica'ons.
57 | 57
ANNOTATING SIMPLE CASES
Becoming Acquainted with Web Apollo. SIMPLE CASES
58 |
• A confirma'on box will warn you if the receiving transcript is not on the same strand as the feature where the new exon originated.
• Check ‘Start’ and ‘Stop’ signals ajer each edit.
58
ADDING EXONS
Becoming Acquainted with Web Apollo. SIMPLE CASES
If transcript alignment data are available and extend beyond your original annota'on, you may extend or add UTRs.
1. Right click at the exon edge and ‘Zoom to base level’.
2. Place the cursor over the edge of the exon un1l it becomes a black arrow then click and drag the edge of the exon to the new coordinate posi'on that includes the UTR.
59 | 59
ADDING UTRs
Becoming Acquainted with Web Apollo. SIMPLE CASES
To add a new spliced UTR to an exis'ng annota'on follow the procedure for adding an exon.
To modify an exon boundary and match data in the evidence tracks: select both the offending exon and the feature with the expected boundary, then right click on the annota'on to select ‘Set 3’ end’ or ‘Set 5’ end’ as appropriate.
60 |
In some cases all the data may disagree with the annota'on, in other cases some data support the annota'on and some of the
data support one or more alterna've transcripts. Try to annotate as many alterna've transcripts as are well supported by the data.
60
MATCHING EXON BOUNDARY TO EVIDENCE
Becoming Acquainted with Web Apollo. SIMPLE CASES
1. Zoom in to clearly resolve each exon as a dis'nct rectangle.
2. Two exons from different tracks sharing the same start and/or end coordinates will display a red bar to indicate matching edges.
3. Selec'ng the whole annota'on or one exon at a 'me, use this ‘edge-‐matching’ func'on and scroll along the length of the annota'on, verifying exon boundaries against available data. Use square [ ] brackets to scroll from exon to exon.
4. Check if cDNA / RNAseq reads lack one or more of the annotated exons or include addi'onal exons.
61 | 61
CHECKING EXON INTEGRITY
Becoming Acquainted with Web Apollo. SIMPLE CASES
Non-‐canonical splice sites flags. Double click: selec'on of feature and sub-‐features
Evidence Tracks Area
‘User-‐created Annota1ons’ Track
Edge-‐matching
Apollo’s edi'ng logic (brain): § selects longest ORF as CDS § flags non-‐canonical splice sites
62
ORFs AND SPLICE SITES
Becoming Acquainted with Web Apollo. SIMPLE CASES
63 |
Non-‐canonical splices are indicated by an orange circle with a white exclama'on point inside, placed over the edge of the offending exon.
Canonical splice sites:
3’-‐…exon]GA / TG[exon…-‐5’
5’-‐…exon]GT / AG[exon…-‐3’ reverse strand, not reverse-‐complemented:
forward strand
63
SPLICE SITES
Becoming Acquainted with Web Apollo. SIMPLE CASES
Zoom to review non-‐canonical splice site warnings. Although these may not always have to be corrected (e.g GC donor), they should be flagged with the appropriate comment.
Exon/intron splice site error warning
Curated model
Web Apollo calculates the longest possible open reading frame (ORF) that includes canonical ‘Start’ and ‘Stop’ signals within the predicted exons.
If ‘Start’ appears to be incorrect, modify it by selec'ng an in-‐frame ‘Start’ codon further up or downstream, depending on evidence (protein database, addi'onal evidence tracks).
It may be present outside the predicted gene model, within a region supported by another evidence track.
In very rare cases, the actual ‘Start’ codon may be non-‐canonical (non-‐ATG).
64 | 64
‘START’ AND ‘STOP’ SITES
Becoming Acquainted with Web Apollo. SIMPLE CASES
complex cases
Evidence may support joining two or more different gene models. Warning: protein alignments may have incorrect splice sites and lack non-‐conserved regions!
1. In ‘User-‐created Annota,ons’ area shij-‐click to select an intron from each gene model and right click to select the ‘Merge’ op'on from the menu.
2. Drag suppor'ng evidence tracks over the candidate models to corroborate overlap, or review edge matching and coverage across models.
3. Check the resul'ng transla'on by querying a protein database e.g. UniProt, NCBI nr. Add comments to record that this annota'on is the result of a merge.
66 | 66
Red lines around exons: ‘edge-‐matching’ allows annotators to confirm whether the evidence is in agreement without examining each exon at the base level.
COMPLEX CASES merge two gene predictions on the same scaffold
Becoming Acquainted with Web Apollo. COMPLEX CASES
One or more splits may be recommended when: -‐ different segments of the predicted protein align to two or more different gene families -‐ predicted protein doesn’t align to known proteins over its en're length
Transcript data may support a split, but first verify whether they are alterna've transcripts.
67 | 67
COMPLEX CASES split a gene prediction
Becoming Acquainted with Web Apollo. COMPLEX CASES
DNA Track
‘User-‐created Annota=ons’ Track
68
COMPLEX CASES correcting frameshifts and single-base errors
Becoming Acquainted with Web Apollo. COMPLEX CASES
Always remember: when annota'ng gene models using Apollo, you are looking at a ‘frozen’ version of the genome assembly and you will not be able to modify the assembly itself.
69
COMPLEX CASES correcting selenocysteine containing proteins
Becoming Acquainted with Web Apollo. COMPLEX CASES
70
COMPLEX CASES correcting selenocysteine containing proteins
Becoming Acquainted with Web Apollo. COMPLEX CASES
1. Apollo allows annotators to make single base modifica'ons or frameshijs that are reflected in the sequence and structure of any transcripts overlapping the modifica'on. These manipula'ons do NOT change the underlying genomic sequence.
2. If you determine that you need to make one of these changes, zoom in to the nucleo'de level and right click over a single nucleo'de on the genomic sequence to access a menu that provides op'ons for crea'ng inser'ons, dele'ons or subs'tu'ons.
3. The ‘Create Genomic Inser=on’ feature will require you to enter the necessary string of nucleo'de residues that will be inserted to the right of the cursor’s current loca'on. The ‘Create Genomic Dele=on’ op'on will require you to enter the length of the dele'on, star'ng with the nucleo'de where the cursor is posi'oned. The ‘Create Genomic Subs=tu=on’ feature asks for the string of nucleo'de residues that will replace the ones on the DNA track.
4. Once you have entered the modifica'ons, Apollo will recalculate the corrected transcript and protein sequences, which will appear when you use the right-‐click menu ‘Get Sequence’ op'on. Since the underlying genomic sequence is reflected in all annota'ons that include the modified region you should alert the curators of your organisms database using the ‘Comments’ sec'on to report the CDS edits.
5. In special cases such as selenocysteine containing proteins (read-‐throughs), right-‐click over the offending/premature ‘Stop’ signal and choose the ‘Set readthrough stop codon’ op'on from the menu.
71 | 71 Becoming Acquainted with Web Apollo. COMPLEX CASES
COMPLEX CASES correcting frameshifts, single-base errors, and selenocysteines
72 | 72
USER NAVIGATION
Becoming Acquainted with Web Apollo.
• Annotation right-click menu
73
Annota'ons, annota'on edits, and History: stored in a centralized database.
73
USER NAVIGATION
Becoming Acquainted with Web Apollo.
Follow the checklist un'l you are happy with the annota'on!
And remember to… – comment to validate your annota'on, even if you made no changes to an exis'ng model. Think of comments as your vote of confidence.
– or add a comment to inform the community of unresolved issues you think this model may have.
74 | 74
Always Remember: Apollo cura'on is a community effort so please use comments to communicate the reasons for your
annota'on. Your comments will be visible to everyone.
COMPLETING THE ANNOTATION
Becoming Acquainted with Apollo.
75 | 75
USER NAVIGATION
Becoming Acquainted with Web Apollo.
• Annotation right-click menu
76
The Annota'on Informa=on Editor
76
USER NAVIGATION
Becoming Acquainted with Web Apollo.
DBXRefs are database crossed references: if you have reason to believe that this gene is linked to a gene in a public database (including your own), then add it here.
77
The Annota'on Informa=on Editor
• Add PubMed IDs • Include GO terms as appropriate
from any of the three ontologies • Write comments sta'ng how you
have validated each model.
77
USER NAVIGATION
Becoming Acquainted with Web Apollo.
Checklist
• Check ‘Start’ and ‘Stop’ sites.
• Check splice sites: most splice sites display these residues …]5’-‐GT/AG-‐3’[…
• Check if you can annotate UTRs, for example using RNA-‐Seq data: – Align it against relevant genes/gene family – blastp against NCBI’s RefSeq or nr
• Check for gaps in the genome.
• Addi'onal func'onality may be necessary: – Merging 2 gene predic'ons on the same scaffold
– Merging 2 gene predic'ons from different scaffolds
– Spligng a gene predic'on – Correc'ng frameshiYs and other errors in the genome assembly
– Annotate selenocysteines, correct single-‐base errors, etc.
79 | 79
• Add: – Important project informa'on in the form of
comments – IDs from public databases e.g. GenBank (via
DBXRef), gene symbol(s), common name(s), synonyms, top BLAST hits, orthologs with species names, and everything else you can think of, because you are the expert.
– Comments about the kinds of changes you made to the gene model of interest, if any.
– Any appropriate func'onal assignments, e.g. via BLAST, RNA-‐Seq data, literature searches, etc.
THE CHECKLIST for accuracy and integrity
MANUAL ANNOTATION CHECKLIST
Example
Example
Example 81
A public Apollo Demo using the Honey Bee genome is available at h@p://genomearchitect.org/WebApolloDemo
-‐ Cura'on example using the Hyalella azteca genome (amphipod crustacean).
What do we know about this genome?
• Currently publicly available data at NCBI: • >37,000 nucleo'de seqsà scaffolds, mitochondrial genes • 300 amino acid seqsà mitochondrion • 53 ESTs • 0 conserved domains iden'fied • 0 “gene” entries submi@ed
• Data at i5K Workspace@NAL (annota'on hosted at USDA) -‐ 10,832 scaffolds: 23,288 transcripts: 12,906 proteins
Example 82
PubMed Search: what’s new?
Example 83
PubMed Search: what’s new?
Example 84
“Ten popula'ons (3 cultures, 7 from California water bodies) differed by at least 550-‐fold in sensi=vity to pyrethroids.”
“By sequencing the primary pyrethroid target site, the voltage-‐gated sodium channel (vgsc), we show that point muta'ons and their spread in natural popula'ons were responsible for differences in pyrethroid sensi'vity.”
“The finding that a non-‐target aqua'c species has acquired resistance to pes'cides used only on terrestrial pests is troubling evidence of the impact of chronic pes=cide transport from land-‐based applica'ons into aqua'c systems.”
How many sequences are there, publicly available, for our gene of interest?
Example 85
• Para, (voltage-‐gated sodium channel alpha subunit; Nasonia vitripennis).
• NaCP60E (Sodium channel protein 60 E; D. melanogaster). – MF: voltage-‐gated ca'on channel ac'vity (IDA, GO:0022843).
– BP: olfactory behavior (IMP, GO:0042048), sodium ion transmembrane transport (ISS,GO:0035725).
– CC: voltage-‐gated sodium channel complex (IEA, GO:0001518).
And what do we know about them?
Retrieving sequences for sequence similarity searches.
Example 86
>vgsc-‐Segment3-‐DomainII RVFKLAKSWPTLNLLISIMGKTVGALGNLTFVLCIIIFIFAVMGMQLFGKNYTEKVTKFKWSQDGQMPRWNFVDFFHSFMIVFRVLCGEWIESMWDCMYVGDFSCVPFFLATVVIGNLVVSFMHR
BLAT search
input
Example 87
>vgsc-‐Segment3-‐DomainII RVFKLAKSWPTLNLLISIMGKTVGALGNLTFVLCIIIFIFAVMGMQLFGKNYTEKVTKFKWSQDGQMPRWNFVDFFHSFMIVFRVLCGEWIESMWDCMYVGDFSCVPFFLATVVIGNLVVSFMHR
BLAT search
results
Example 88
• High-‐scoring segment pairs (hsp) are listed in tabulated format.
• Clicking on one line of results sends you to those coordinates.
Creating a new gene model: drag and drop
Example 89
• Apollo automatically calculates ORF. In this case, ORF includes the high-scoring segment pairs (hsp), marked here in blue.
Available Tracks
Example 90
Get Sequence
Example 91
http://blast.ncbi.nlm.nih.gov/Blast.cgi
Also, flanking sequences (other gene models) vs. NCBI nr
Example 92
In this case, two gene models upstream, at 5’ end.
BLAST hsps
Review alignments
Example 93
HaztTmpM006234
HaztTmpM006233
HaztTmpM006232
Hypothesis for vgsc gene model
Example 94
Editing: merge the three models
Example 95
Merge by dropping an exon or gene model onto another.
Merge by selec'ng two exons (holding down “Shij”) and using the right click menu.
or…
Result of merging the three models.
Example 96
Editing: correct boundaries
Example 97
Modify exon / intron boundary: -‐ Drag the end of the
exon to the nearest canonical splice site.
or
-‐ Use right-‐click menu.
Editing: set translation start
Example 98
Editing: delete exon
Example 99
Delete first exon from HaztTmpM006233
Editing: add an exon - supported by RNAseq
Example 100
• RNAseq reads show evidence in support of transcribed product, which was not predicted. • Add exon at coordinates 97946-‐98012 by dragging up one of the RNAseq reads.
Editing: and adjust other exon boundary using evidence
Example 101
Editing: adjust other boundaries supported by evidence
Example 102
Finished model
Example 103
Corroborate integrity and accuracy of the model: -‐ Start and Stop -‐ Exon structure and splice sites …]5’-‐GT/AG-‐3’[… -‐ Check the predicted protein product vs. NCBI nr, UniProt, etc.
Information Editor
• DBXRefs: e.g. NP_001128389.1, N. vitripennis, RefSeq
• PubMed iden'fier: PMID: 24065824
• Gene Ontology IDs: GO:0022843, GO:0042048, GO:0035725, GO:0001518.
• Comments.
• Name, Symbol.
• Approve / Delete radio bu@on.
Example 104
Comments (if applicable)
Demo
APOLLOdemonstration
DEMO 106
Demo video is available at h@ps://youtu.be/VgPtAP_fvxY
OUTLINE
Web Apollo Collabora've Cura'on and Interac've Analysis of Genomes
107 OUTLINE
• BIO-‐REFRESHER biological concepts for cura'on
• ANNOTATION automa'c predic'ons
• MANUAL ANNOTATION necessary, collabora've
• APOLLO
advancing collabora've cura'on • EXAMPLE
demos
• EXERCISES
Exercises
Exercises Live Demonstra'on using the Apis mellifera genome.
110
1. Evidence in support of protein coding gene models. 1.1 Consensus Gene Sets: Official Gene Set v3.2 Official Gene Set v1.0 1.2 Consensus Gene Sets comparison: OGSv3.2 genes that merge OGSv1.0 and RefSeq genes OGSv3.2 genes that split OGSv1.0 and RefSeq genes 1.3 Protein Coding Gene Predic=ons Supported by Biological Evidence: NCBI Gnomon Fgenesh++ with RNASeq training data Fgenesh++ without RNASeq training data NCBI RefSeq Protein Coding Genes and Low Quality Protein Coding Genes
1.4 Ab ini,o protein coding gene predic=ons: Augustus Set 12, Augustus Set 9, Fgenesh, GeneID, N-‐SCAN, SGP2 1.5 Transcript Sequence Alignment: NCBI ESTs, Apis cerana RNA-‐Seq, Forager Bee Brain Illumina Con'gs, Nurse Bee Brain Illumina Con'gs, Forager RNA-‐Seq reads, Nurse RNA-‐Seq reads, Abdomen 454 Con'gs, Brain and Ovary 454 Con'gs, Embryo 454 Con'gs, Larvae 454 Con'gs, Mixed Antennae 454 Con'gs, Ovary 454 Con'gs Testes 454 Con'gs, Forager RNA-‐Seq HeatMap, Forager RNA-‐Seq XY Plot, Nurse RNA-‐Seq HeatMap, Nurse RNA-‐Seq XY Plot
Becoming Acquainted with Web Apollo.
Exercises Live Demonstra'on using the Apis mellifera genome.
111
1. Evidence in support of protein coding gene models (Con=nued). 1.6 Protein homolog alignment: Acep_OGSv1.2 Aech_OGSv3.8 Cflo_OGSv3.3 Dmel_r5.42 Hsal_OGSv3.3 Lhum_OGSv1.2 Nvit_OGSv1.2 Nvit_OGSv2.0 Pbar_OGSv1.2 Sinv_OGSv2.2.3 Znev_OGSv2.1 Metazoa_Swissprot
2. Evidence in support of non protein coding gene models 2.1 Non-‐protein coding gene predic=ons: NCBI RefSeq Noncoding RNA NCBI RefSeq miRNA 2.2 Pseudogene predic=ons: NCBI RefSeq Pseudogene
Becoming Acquainted with Web Apollo.
Instrucciones 112 | 112
APOLLO ON THE WEBinstructions
Username: [email protected]
Password: usernumber
Email Password Server Begin at [email protected] userone 1 1 [email protected] usertwo 2 1 [email protected] userthree 3 1 [email protected] userfour 4 1 [email protected] userfive 5 1 [email protected] usersix 1 7 [email protected] userseven 2 7 [email protected] usereight 3 7 [email protected] usernine 4 7 [email protected] userten 5 7 [email protected] usereleven 1 1 [email protected] usertwelve 2 1 [email protected] userthirteen 3 1 [email protected] userfourteen 4 1 [email protected] userfijeen 5 1 [email protected] usersixteen 1 7 [email protected] userseventeen 2 7 user.eigh@[email protected] usereighteen 3 7 [email protected] usernineteen 4 7 [email protected] usertwenty 5 7 [email protected] usertwentyone 1 1 [email protected] usertwentytwo 2 1 [email protected] usertwentythree 3 1 [email protected] usertwentyfour 4 1 [email protected] usertwentyfive 5 1 [email protected] usertwentysix 1 7 [email protected] usertwentyseven 2 7 [email protected] usertwentyeight 3 7 [email protected] usertwentynine 4 7
Server URL 1 h@p://52.26.7.239:8080/apollo/annotator/index 2 h@p://52.89.205.105:8080/apollo/annotator/index 3 h@p://52.89.230.210:8080/apollo/annotator/index 4 h@p://52.89.149.42:8080/apollo/annotator/index 5 h@p://52.89.233.118:8080/apollo/annotator/index
Thank you. 113
• Berkeley Bioinforma=cs Open-‐source Projects (BBOP), Berkeley Lab: Apollo and Gene Ontology teams. Suzanna E. Lewis (PI).
• § Chris1ne G. Elsik (PI). University of Missouri.
• * Ian Holmes (PI). University of California Berkeley.
• Arthropod genomics community: i5K Steering Commi@ee (esp. Sue Brown (Kansas State)), Alexie Papanicolaou (UWS), and the Honey Bee Genome Sequencing Consor'um.
• Stephen Ficklin, GenSAS, Washington State University
• Apollo is supported by NIH grants 5R01GM080203 from NIGMS, and 5R01HG004483 from NHGRI. Both projects are also supported by the Director, Office of Science, Office of Basic Energy Sciences, of the U.S. Department of Energy under Contract No. DE-‐AC02-‐05CH11231
•
• For your a*en=on, thank you!
Apollo
Nathan Dunn
Colin Diesh §
Deepak Unni §
Gene Ontology
Chris Mungall
Seth Carbon
Heiko Dietze
BBOP
Apollo: h@p://GenomeArchitect.org
GO: h@p://GeneOntology.org
i5K: h@p://arthropodgenomes.org/wiki/i5K
Thank you!
NAL at USDA
Monica Poelchau
Christopher Childers
Gary Moore
HGSC at BCM
fringy Richards
Kim Worley
JBrowse Eric Yao *